CE 394K.2 Surface Water Hydrology Lecture 1 – Introduction to the course Readings for today Applied Hydrology, Chapter 1 “Once more unto the breach, dear friends, once more; Or close the wall up with our English dead! In peace there’s nothing so becomes a man As modest stillness and humility: But when the blast of war blows in our ears, Then imitate the action of the tiger…..” King Henry V before the battle of Agincourt, 1415 Shakespeare, King Henry the Fifth, Act III, Scene I

How is new knowledge discovered? After completing this Handbook in 1993, I asked myself the question: how is new knowledge discovered in hydrology? I concluded that there are three ways: By deduction from existing knowledge By experiment in a laboratory By observation of the natural environment

Deduction – Newton Deduction is the classical path of mathematical physics Given a set of axioms Then by a logical process Derive a new principle or equation In hydrology, the St Venant equations for open channel flow and Richard’s equation for unsaturated flow in soils were derived in this way. Three laws of motion and law of gravitation http://en.wikipedia.org/wiki/Isaac_Newton (1687)

Foundations of scientific medicine Experiment – Pasteur Experiment is the classical path of laboratory science – a simplified view of the natural world replicated under controlled conditions In hydrology, Darcy’s law for flow in a porous medium was found this way. Pasteur showed that microorganisms cause disease & discovered vaccination Foundations of scientific medicine http://en.wikipedia.org/wiki/Louis_Pasteur

Observation – Darwin Observation – direct viewing and characterization of patterns and phenomena in the natural environment In hydrology, Horton discovered stream scaling laws by interpretation of stream maps Published Nov 24, 1859 Most accessible book of great scientific imagination ever written

Conclusion for Hydrology Deduction and experiment are important, but hydrology is primarily an observational science discharge, water quality, groundwater, measurement data collected to support this (USGS)

Hydrologic Science and Engineering Hydrologic Processes (inferred) Physical environment (characterized) Hydrologic conditions (observed) Hydrologic Science In science, we observe conditions and infer processes In engineering, we simulate processes and predict conditions Both require characterizing the surrounding environment Hydrologic Processes (simulated) Physical environment (characterized) Hydrologic conditions (predicted) Hydrologic Engineering

Hydrologic Science It is as important to represent hydrologic environments precisely with data as it is to represent hydrologic processes with equations Physical laws and principles (Mass, momentum, energy, chemistry) Hydrologic Process Science (Equations, simulation models, prediction) Hydrologic conditions (Fluxes, flows, concentrations) Hydrologic Information Science (Observations, data models, visualization Hydrologic environment (Physical earth)

Water quantity and quality Water Data Water quantity and quality Soil water Rainfall & Snow Modeling Meteorology Remote sensing

Water Data Web Sites

NWISWeb site output Time series of streamflow at a gaging station # agency_cd Agency Code # site_no USGS station number # dv_dt date of daily mean streamflow # dv_va daily mean streamflow value, in cubic-feet per-second # dv_cd daily mean streamflow value qualification code # # Sites in this file include: # USGS 02087500 NEUSE RIVER NEAR CLAYTON, NC agency_cd site_no dv_dt dv_va dv_cd USGS 02087500 2003-09-01 1190 USGS 02087500 2003-09-02 649 USGS 02087500 2003-09-03 525 USGS 02087500 2003-09-04 486 USGS 02087500 2003-09-05 733 USGS 02087500 2003-09-06 585 USGS 02087500 2003-09-07 485 USGS 02087500 2003-09-08 463 USGS 02087500 2003-09-09 673 USGS 02087500 2003-09-10 517 USGS 02087500 2003-09-11 454 Time series of streamflow at a gaging station USGS has committed to supporting CUAHSI’s GetValues function

Observation Stations Map for the US Ameriflux Towers (NASA & DOE) NOAA Automated Surface Observing System David - for each of these site files, can you include how many points are in each one. USGS National Water Information System NOAA Climate Reference Network

Water Quality Measurement Sites in EPA Storet Substantial variation in data availability from states Data from Bora Beran, Drexel University

Water Quality Measurement Sites from Texas Commission for Environmental Quality (TCEQ)

Geographic Integration of Storet and TCEQ Data in HIS

and how many observations of each variable are available Observations Catalog Specifies what variables are measured at each site, over what time interval, and how many observations of each variable are available

CUAHSI Hydrologic Data Access System (being built using HIS Server in collaboration with ESRI) NCDC NASA EPA NWS Observatory Data USGS David – This slide implies that the CUAHSI website is the path through which people would access this data. I’m not sure that this is really your intent, since the fed agencies are not CUAHSI members and in the long run would probably access this data and use these tools through another path. But the line at the bottom of the slide should appear somewhere, as it is one of the key messages, if not THE key message. How do you feel about changing the labeling on this slide to be more consistent since it’s a fed agency audience. Either list agencies, list data sources, or list both. So USGS could be listed as USGS, as NWIS, or as USGS NWIS EPA as EPA, STORET or EPA STORET NCDC as NOAA, NCDC or NOAA NCDC NWS as NOAA-NWS or NDFD, or NOAA NDFD NASA – any specific datasets or websites like Giovanni? A common data window for accessing, viewing and downloading hydrologic information

HIS Server Supports data discovery, delivery and publication Data discovery – how do I find the data I want? Map interface and observations catalogs Metadata based Search Data delivery – how do I acquire the data I want? Use web services or retrieve from local database Data Publication – how do I publish my observation data? Use Observations Data Model

HIS Server and Analyst HIS Server HIS Analyst Implemented at San Diego Supercomputer Center and at academic departments and research centers Implemented by individual hydrologic scientists using their own analysis environments Web Services Flexible – any operating system, model, programming language or application Sustainable – industrial strength technology http://www.cuahsi.org/his/webservices.html Details of HIS Analyst are here

Point Observations Information Model http://www.cuahsi.org/his/webservices.html USGS Data Source Streamflow gages Network Neuse River near Clayton, NC Sites Discharge, stage (Daily or instantaneous) Variables Values 206 cfs, 13 August 2006 {Value, Time, Qualifier} A data source operates an observation network A network is a set of observation sites A site is a point location where one or more variables are measured A variable is a property describing the flow or quality of water A value is an observation of a variable at a particular time A qualifier is a symbol that provides additional information about the value

Data Sources Extract Transform CUAHSI Web Services Load Applications NASA Storet Ameriflux Extract NCDC Unidata NWIS NCAR Transform CUAHSI Web Services Excel Visual Basic Shauna – the ones on top are a bunch of web sites providing data that go through the CUAHSI Web Services (basically some software) which allows all this data to be used in all these other software packages listed across the bottom. The ones in red are the ones that are connections that are already built. It would look good to redo this in ESRI style. ArcGIS C/C++ Load Matlab Fortran Access Java Applications http://www.cuahsi.org/his/ Some operational services

CUAHSI Web Services Your application Your operating system Web Application: Data Portal Your application Excel, ArcGIS, Matlab Fortran, C/C++, Visual Basic Hydrologic model ……………. Your operating system Windows, Unix, Linux, Mac Internet Simple Object Access Protocol Web Services Library

Series and Fields Features Series – ordered sequence of numbers Point, line, area, volume Discrete space representation Time series – indexed by time Frequency series – indexed by frequency Surfaces Fields – multidimensional arrays Doug: Could you please add a point, line, area symbols or something generic that represents features. Continuous space representation Scalar fields – single value at each location Vector fields – magnitude and direction Random fields – probability distribution

North American Regional Reanalysis of Climate Precipitation Evaporation Variation during the day, July 2003 NetCDF format mm / 3 hours

Data Cube – What, Where, When Space, L Time, T Variable, V D “When” A data value “Where” “What”

Continuous Space-Time Data Model -- NetCDF Time, T Coordinate dimensions {X} D Space, L Variable dimensions {Y} Variables, V

Discrete Space-Time Data Model Time, TSDateTime TSValue Space, FeatureID Variables, TSTypeID

Hydrologic Statistics Time Series Analysis Geostatistics Multivariate analysis How do we understand space-time correlation fields of many variables?

Project sponsored by the European Commission to promote integration of water models within the Water Framework Directive Software standards for model linking Uses model core as an “engine” http://www.openMI.org

OpenMI – Links Data and Simulation Models Simple River Model Trigger (identifies what value should be calculated) CUAHSI Observations Data Model as an OpenMI component

Typical model architecture Model application Application User interface + engine Engine Simulates a process – flow in a channel Accepts input Provides output Model An engine set up to represent a particular location e.g. a reach of the Thames User interface Write Input data Run Read An engine simulates a process – water flowing in a channel An engine +data is a model of a particular process – the Rhine Engine Write Output data

Linking modelled quantities Rainfall Runoff Model River Model Accepts Provides Upstream Inflow (m3/s) Outflow Lateral inflow Abstractions Discharges Accepts Provides Rainfall (mm) Runoff (m3/s) Temperature (Deg C) Evaporation

Data transfer at run time Rainfall runoff Output data Input data User interface River GetValues(..)

Models for the processes Rainfall (database) RR (Sobek-Rainfall -Runoff) River (InfoWorks RS) Sewer (Mouse)

Data exchange 3 Rainfall.GetValues 4 2 RR.GetValues Rainfall (database) 4 RR (Sobek-Rainfall -Runoff) 2 RR.GetValues 1 Trigger.GetValues 5 7 RR.GetValues 8 River (InfoWorks-RS) call Sewer (Mouse) 6 Sewer.GetValues 9 data

Water OneFlow Like Geospatial OneStop, we need a “Water OneFlow” – a common window for water data and models Advancement of water science is critically dependent on integration of water information Federal Academic Local State